Results 151 to 160 of about 3,473 (211)

Combining predictive accuracy and interpretability: a data-driven approach to telecom churn analysis. [PDF]

Sci Rep
Hooda P, Mittal P, Shukla PK, Shukla PK, Pandey A.   +4 more
europepmc   +1 more source

Predicting Customer Churn in E-commerce

Customer retention has become a critical focus for businesses seeking to sustain growth and profitability in an increasingly competitive market. In this thesis, advanced machine learning techniques are used to develop a data-driven churn prediction model
Kazim, Hind Tawfiq
core  

Marketing-AutoM3L: domain-aware automated machine learning for financial customer analytics. [PDF]

Front Artif Intell
Tian Y, Shao W, Deng Z.
europepmc   +1 more source

Integrating Business Intelligence and CRM Systems With a Machine Learning Approach for Predictive Customer Retention in E-Commerce. [PDF]

ScientificWorldJournal
Zeinali M, Ramezani Asli L, Khalili MA.
europepmc   +1 more source

AIM2 framework for smart marketing innovation using AI driven consumer analytics with SOR neural networks and XGBoost in Saudi retail. [PDF]

Sci Rep
Alarfaj FK, Badouch M, Khan HU, Boutaounte M.   +3 more
europepmc   +1 more source

A comprehensive dataset of customer behavior in Latin American Fintech: 12-month transactional and demographic data for churn analysis. [PDF]

Data Brief
Muñoz-Guerrero LE, Ceballos YF, Trejos-Rojas LD.   +2 more
europepmc   +1 more source

Marketing analytics in banking 4.0: A two-stage explainable AI framework for high-accuracy and well-calibrated predictions. [PDF]

PLoS One
Nasir F, Ali Ahmed A, Yevseyeva I, Kiraz MS.   +3 more
europepmc   +1 more source

Early viability assessment of a Business-to-Consumer (B2C) model for digital diabetes screening in Switzerland. [PDF]

BMC Health Serv Res
Mekniran W, Kowatsch T.
europepmc   +1 more source

Predicting customer loyalty in omnichannel retailing using purchase behavior, socio-cultural factors, and learning techniques. [PDF]

PLoS One
Roosta S, Sadjadi SJ, Makui A.
europepmc   +1 more source

Predicting repurchase behavior and optimizing marketing for e-commerce users with genetic algorithms and deep learning. [PDF]

Sci Rep
Yang S.
europepmc   +1 more source